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WebFeature specifications


Unique identifier OMICS_12673
Name WebFeature
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Version 3.1
Stability No
Maintained No




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This tool is not available anymore.


Unique identifier OMICS_12673
Name WebFeature
Interface Web user interface
Restrictions to use None
Input format pdb, Protein Data Bank ID
Computer skills Basic
Version 4.0
Stability No
Maintained No


This tool is not available anymore.

Publication for WebFeature

WebFeature citations


Biochemical Characterization of the SPATE Members EspPα and EspI

PMCID: 4179157
PMID: 25229188
DOI: 10.3390/toxins6092719

[…] the suggestion that it is important for the stability of this protease []. Notably, the investigation of potential calcium-binding sites within the crystal structure of EspPα (pdb: 3SZE) [] using the WebFEATURE program [] indicated that Ca2+ binding might occur at the interfacing α-helical region connecting the proteolytic domain1 and the β-helical backbone as well as in loop 165 (data not shown). […]


Catalytic residues in hydrolases: analysis of methods designed for ligand binding site prediction

J Comput Aided Mol Des
PMCID: 3032897
PMID: 21104192
DOI: 10.1007/s10822-010-9402-0
call_split See protocol

[…] The computations were performed using standalone executables (FOD, PASS version 2.0.36), web services made in Ruby able to communicate with CASTp, ConSurf, Pocket-Finder, Q-SiteFinder, WebFEATURE and text queries offered by SuMo server. Additionally, the precalculated results were downloaded from ConSurfDB []. Only the highest ranked pockets/predictions were considered. The outputs […]


BSSF: a fingerprint based ultrafast binding site similarity search and function analysis server

BMC Bioinformatics
PMCID: 3098077
PMID: 20100327
DOI: 10.1186/1471-2105-11-47

[…] milarity between the two binding sites. This represents a more natural way to describe the shape and properties of a binding site, especially where two binding sites only share sub-pocket similarity. WebFeature is another ultrafast binding site similarity comparison and functional annotation system[]. It uses the calculated biophysical properties of binding sites to represent the binding site and […]


Prediction of calcium binding sites by combining loop modeling with machine learning

BMC Struct Biol
PMCID: 2808310
PMID: 20003365
DOI: 10.1186/1472-6807-9-72

[…] Calcium-binding sites were predicted using FEATURE. A complete description of FEATURE can be found in the original paper and a web server of FEATURE is also provided in http://feature.stanford.edu/webfeature[]. In summary, we make observations of 66 physical-chemical properties on a dataset of experimentally determined structures containing calcium-binding sites. We then compile a conditional p […]


The FEATURE framework for protein function annotation: modeling new functions, improving performance, and extending to novel applications

BMC Genomics
PMCID: 2559884
PMID: 18831785
DOI: 10.1186/1471-2164-9-S2-S2

[…] FEATURE models, data, and source code are available online for public use. The WebFEATURE website [,] allows functional scans of PDB structures using any of the manually curated models or the models in the SeqFEATURE library, as well as the option to scan using the entire SeqFEA […]


The SeqFEATURE library of 3D functional site models: comparison to existing methods and applications to protein function annotation

Genome Biol
PMCID: 2395245
PMID: 18197987
DOI: 10.1186/gb-2008-9-1-r8

[…] All of the models may be used to scan any protein structure on WebFEATURE, our web-accessible function prediction server []. Results from the PDB scan are also available for download. Source code for FEATURE is available from SimTK []. […]

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WebFeature institution(s)
Department of Computer Science, San Francisco State University, San Francisco, CA, USA; Center for Computing for Life Sciences, San Francisco State University, San Francisco, CA, USA; Department of Bioengineering, Stanford University, Stanford, CA, USA
WebFeature funding source(s)
Supported by an Amazon Web Services in Education Research Grant to Center for Computing for Life Sciences at San Francisco State University, awarded June 18, 2012; by NIH grants LM05652, GM072970, GM102365 and the NSFBIOX2 award CNS-0619926.

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